Second cycle degree in

Data science

Class: LM-91 - Methods and techniques for the information society

Logo QS
Class LM-91 - Methods and techniques for the information society
Duration 2 years
Branch Padova
Language English
Tuition fees and scholarships
Programme coordinator FRANCESCO RINALDI
Access Open access with admission requirements

Next Calls for applications (international students) - A.Y. 2022/23:

  • 1st Call: 2 November 2021-2 February 2022
  • 2nd Call: 2 March-2 May 2022 (non-EU)/2 September (EU) - APPLY NOW

The Data Science Master's programme is conceived as a multi-disciplinary platform that covers a broad range of theories and tools coming from different fields like, e.g., engineering, computer science, mathematics, statistics, machine learning, artificial intelligence. Through this programme, you will learn to handle and process big amounts of data, obtaining highly valuable information for the decisional processes. You may choose between four curricula with a specific focus on areas closely intertwined with big data analysis. You will be able to work in companies that provide IT services, startups and high-tech companies, public institutions and research centers. The course is entirely delivered in English. Curricula: - Biological Data Analytics - Cognitive, Social and Economic Data Analytics - Machine Learning for Intelligent Systems - Mathematics of Data Science Erasmus Mundus Joint Master Degree BDMA - Big Data Management and Analytics

Curricula
BDMA; Data Science

  Find out more

Characteristics and objectives
The program intends to build Data Scientists whose solid technical background is complemented by a multidisciplinary preparation on various fields in which big data emerge. Highly required by Industries, Consulting Companies and Public Institutions, Data Scientists design and implement the analysis of big data, and provide managers and stakeholders with a clear account of their results. The Graduated in this degree will be able to master tools coming from Engineering, Computer Sciences, Statistics and Mathematics for collecting, managing and analyzing big data, and to translate their work into highly valuable informations.

Occupational opportunities
The Graduates will have jobs opportunity in Italy and abroad in
▪ internet companies, consulting companies;
▪ startups and high tech industries;
▪ public administrations;
▪ research centers.

Curricula
BDMA; Data Science

  Teaching list

I Year OPTIMIZATION FOR DATA SCIENCE [CFU 6] STATISTICAL LEARNING 2 (MOD. B) [CFU 6] STATISTICAL LEARNING 1 (MOD. A) [CFU 6] STATISTICAL LEARNING (C.I.) [CFU 0] OMICS IN HUMAN DISEASE [CFU 6] INTRODUCTION TO MOLECULAR BIOLOGY [CFU 6] SYSTEMS BIOLOGY [CFU 6] MATHEMATICAL CELL BIOLOGY [CFU 6] LAW AND DATA [CFU 6] STOCHASTIC METHODS [CFU 6] FINANCIAL MATHEMATICS FOR DATA SCIENCE [CFU 6] HIGH DIMENSIONAL PROBABILITY FOR DATA SCIENCE [CFU 6] MATHEMATICAL MODELS AND NUMERICAL METHODS FOR BIG DATA [CFU 6] HUMAN COMPUTER INTERACTION [CFU 6] STRUCTURAL BIOINFORMATICS [CFU 6] GAME THEORY [CFU 6] PROCESS MINING [CFU 6] COGNITION AND COMPUTATION [CFU 6] DEEP LEARNING [CFU 6] FUNDAMENTALS OF INFORMATION SYSTEMS [CFU 12] KNOWLEDGE AND DATA MINING [CFU 6] MACHINE AND DEEP LEARNING (MOD. A) [CFU 6] MACHINE AND DEEP LEARNING (MOD. B) [CFU 6] NETWORK SCIENCE [CFU 6] HUMAN DATA ANALYTICS [CFU 6] BIG DATA COMPUTING [CFU 6] INFORMATION RETRIEVAL [CFU 6] MACHINE AND DEEP LEARNING (C.I.) [CFU 0]